Content analysis

In case studies there tends to be significant amounts of data because respondents are given some scope to express themselves freely; this amount of data can overwhelm the researcher in his/her attempt to analyse it (Ghauri & Gronhaug, 2010). To deal with this, content analysis is applied to seek structures and consistencies in the data collected (Myers, 2009). Devlin (2006, p. 198) summarised the steps in a content analysis below:

1) read through all the written responses 2) create a condensed list of the responses

3) create a list of categories (no more than six or seven) 4) develop an operational definition for each category

5) conduct inter-rater reliability analyses on a sample of each category.

Codes function as shorthand strategies to distinguish, label, compile and consolidate data to make it easy to manage information for the purpose of interpretation. Hesse-Biber and Leavy (2011) view content analysis as a cyclical or ‗spiral‘ approach to knowledge-building, where data are cumulatively analysed bit by bit. Here ―... the researcher generates new understandings with varied levels of specificity, during each phase of the project and uses this information to double back and gain more information‖ (p. 234). This design is shown in Figure 5.3.

114 Embodied interpretation Analyse additional data Analyse sub-set of data Generate codes (literal to abstract) Re-analyse data. Analyse additional data Memo notes Refine codes. Generate meta-codes Representation Topical area

Figure 5.3 Content analysis flowchart: Qualitative model (inductive)

Source: Neuendorf (2001) cited in Hesse-Biber & Leavy (2011, p. 234).

According to Hesse-Biber and Leavy (2011) the researcher starts with a topic and research questions; codes are generated from the data under study; and then the researcher doubles back to re-examine data applying the new code categories. Although these steps may not be followed as precisely as presented, they act as a guide to systematic data analysis and interpretation.

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1. All the data collected from different sources were merged and read through.

2. All items of data that shared common characteristics were classified into categories that were based on the three phases of a developed T&D framework.

3. Statements were developed to define each category.

4. The data were coded by identifying any patterns, sequence or system in the recorded information. Baker and Foy (2008) differentiate classification and coding thus: ―classification is concerned with the creation of categories, while coding is the technique used to assign the raw data to the correct category‖ (p. 294).

5. The researcher and a fellow PhD student separately examined a sample of the data and placed different definitions into their correct category. The two sets of coded data were then compared and found to closely correlate. This was done to develop inter-rater reliability by allowing an independent judge to place the operational definitions into their rightful categories.

5.6 Measures of consistency

In most research a primary concern is with validity and reliability. Webb (2000 as cited by Baker and Foy 2008) notes that validity is the extent to which a tool measures what it is expected to measure, whereas reliability denotes the consistency of achieving similar results when the measure is repeated. Therefore, while valid measures will always be reliable, a reliable measure may not always be valid (Baker & Foy, 2008).

5.6.1 Validity

Qualitative research has a high concern for internal validity because qualitative measures are not statistically tested, and most data are collected through verbal methods that are difficult to measure. In addition the multiplicity of data adds to the real threat to internal validity and calls for the researcher to be extra vigilant. In this study, FG discussions proved the most divergent of the responses and the researcher often had to ask for clarification and consensus where the outlook was divided. In addition, to address opposing explanations, different responses were checked for similarity in pattern and account to ensure that a third factor was not the cause of the explanation, as recommended by Yin (2008). Amerson (2011) further adds that one can accomplish internal validity by using various methods such as pattern matching, explanation building, using logic models, or addressing rival explanations.

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To deal with construct validity, the researcher used multiple sources of evidence and had the respondents review recorded data to ascertain its authenticity. This is in line with recommendations by Amerson (2011, p. 428), that ―construct validity is established by using multiple sources of evidence, maintaining a chain of evidence, and having a key informant review the draft of the case study report or through member checking‖. Furthermore, all taped interviews and discussions were kept safely and referred to during analysis to clarify any ambiguous statements. To clarify vague statements and contradictory information during the interview process, opinions were sought from colleague respondents. In addition, the researcher explained technical terms, and in some instances she translated the study‘s interview questions to the national language (Kiswahili) to avoid misrepresentation of facts.

External validity defines the extent to which particular research findings can be generalised to other populations and to the broader world (Devlin, 2006), and the extent to which the outcome of a study in one or more instances applies to others that have not been studied (Dul & Hak, 2008). In this research project 19 MSE in the MVRSI and four training institutions were used to collect data that was deemed sufficient. Although this sample is not sufficient for generalisation, the research provokes more study by presenting multiple views from the stakeholders in the MVRSI, which can be replicated for other industries.

Curran and Blackburn (2001) identified seven ‗maxims‘ for establishing validity in qualitative research, five of which were relevant to this research:

 The statement of the problem is expressed clearly and precisely.  All key concepts and assumptions are stated clearly and precisely.

 The methodology is systematic, clear and adequate. In this study case study methodology was used.

 The methods of analysis is precise about elements of interpretation and the logic linking the those elements

 The research determines whether the implications for policy and practice receive sufficient attention.

To address these assertions and questions, the following activities were carried out. The statement of the problem was clearly and precisely stated in Chapter 1 and repeated at the beginning of this

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chapter, and this was communicated to all the participants of this research. The study objectives and research questions were also clearly presented in Chapter 1 and the research methods have been described in this chapter. Analysis of the data was done using content analysis and presented using simple frequency measurements, and the interpretations presented in the next three chapters. Lastly, a summary detailing the implications of the findings has been established and recommendations for further research have been made in the last chapter of this study.

5.6.2 Reliability

Reliability is defined as the degree of consistency with which instances are assigned to the same category by the same observer or different observers (Silverman, 2005). While quantitative research views reliability in terms of the consistency in measures, qualitative researchers argue that attention to reliability of research study results should not be ignored (Kirk & Miller, 1989 as cited by Silverman, 2005). Reliability in qualitative research focuses on the perspectives of a number of observers and the reality‘s constantly changing characteristics. Goodwin and Goodwin (1984) argued that reliability is a critical issue for two main reasons: to help ensure replicability of research findings and to provide a necessary prerequisite for validity. The authors outline four types of reliability that are relevant to qualitative measurements:

 Inter-observer, inter-interviewer, inter-recorder reliability, and inter–analyst reliability. This refers to the extent of agreement among two or more observers in the data collection phase and the extent to which independent analysts agree on the identification of data segments to be coded and classified.

 Intra-observer, intra-interviewer, or intra-recorder reliability and intra-analyst reliability. This refers to the extent of consistency of data collection techniques that observers, interviewers and recorders use, and the extent of consistency to which a single researcher identifies the same data segments for coding, classifying and categorising.

 Stability. This refers to the extent of repeatability of observed behaviour or attitudes expressed by the respondents.

 Internal consistency. This refers to the degree of homogeneity in the approach, scheme or schedule used during data collection, and the extent of homogeneity of placing data segments in each derived category.

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Neuman (2003) refers to internal consistency data collection in terms of gathering data in field observation as the researcher checking whether the data gathered is reasonable, whether it fits together, whether it adds up, and whether there is consistency in observable behaviour over time and in different circumstances. He adds that external consistency is attained by verifying or cross- checking data gathered from divergent sources and methods, and argues that reliability is influenced by the researcher‘s questions, insights, cognisance and suspicions; the researcher looks at the study‘s respondents and procedures from different perspectives (economic, political, legal and personal) and mentally seeks answers. Thus any changes in phenomenon over time should be due to observed variations rather than to the method of data collection (Cuneo & Sanders, 2010). To ensure reliability of this research, the following activities were carried out:

 First, interviewees were contacted by phone at least a day before the interview, both to confirm the appointment and to inform them of the topic and particular areas of concern. They were encouraged to bring any relevant documents that would support or confirm their assertions, and the researcher took hand-written notes to record the conversations.  Second, the focus group discussions were all taped using an audio recorder and field

notes. The data were later transcribed by the use of Nvivo soft-ware and used for analysis.  Third, the researcher compared data collected from multiple sources to authenticate them.

Categories and codes were established and then data were placed into these.

 Fourth, the researcher sought the help of a fellow PhD student to re-examine a sample of data and place different definitions into categories.

5.7 Ethical issues

Ethics is defined as the ―use of moral ideologies in designing, conducting, and writing the research outcomes, with the essential moral standards focusing on the right and the wrong‖ (McNabb, 2002, p. 36). In qualitative research, ethics involves protection and respect for respondents taking part in the study (Payne & Payne, 2004). Questionable practices, such as intrusion into people‘s privacy, or exerting influence by offering inducements, are matters of concern that need to be addressed by professional bodies (Baker & Foy, 2008). Debatable issues that have been identified by Robson (2002) include inducing non-consenting individuals, coercion or deception, withholding research information or benefits, deception, violation of self- determination, exposing participants to physical or mental stress and invasion of privacy.

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In this study every effort has been made to ensure that data collection and interpretation conformed to ethical standards as set out by the Edith Cowan University‘s guidelines (ECU2010, p. 1), which state that:

 The welfare and rights of the participants take precedence over the expected benefits to human knowledge.

 The free and informed consent of participants involved in research projects is obtained; and

 Research projects take into account local, cultural and social attitudes.

To comply with the ECU standards of ethics, approval for this research project was granted on 25 October 2010 and assigned project number 5902. Furthermore, this research complied with requirements of section 1.6 of the National Statement on Ethical Conduct in Human Research (2007) which states that ―Researchers must foster and maintain a research environment of intellectual honesty and integrity, and scholarly and scientific rigour‖ (Australian Government, 2007).

To safeguard this study‘s research ethics, all respondents were made aware of their rights in participating in the study. They signed an informed consent form (see Appendix 8), which outlined the following:

 purpose of the study

 identity of the researcher (address, email and location), supervisors and learning institution

 respondent‘s role in the research  degree of confidentiality

 use of data and its storage

 process for termination of involvement at any time and for any reason (see appendix 9). Sensitivity to the respondents‘ personal information, for example income levels, was considered, with a range of figures being used for collecting information to determine income instead of a definite number. Furthermore, interview questions were made simple and clear to avoid any misunderstandings and avoid ambiguity. Technical terminologies was defined and explained, and the interview appointments were set and communicated before the actual date. Courtesy was

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observed during the interview and the respondents were allowed sufficient time to answer questions.

All sources of secondary data have been appropriately acknowledged through their words being paraphrased, summarised or quoted to avoid any case of plagiarism. The research was done in a transparent and accountable manner; the respondents were assured of anonymity and confidentiality and they were offered a soft copy of the finished thesis on request. All efforts were made to conceal the identities of any personal documents used in the study (e.g. financial statements or business meeting minutes). Data collected in the form of transcripts, questionnaires, coded information and analysed data, both soft and hard, were stored in lockable cupboards.

5.8 Summary

The development of the research design has been discussed in this chapter, by outlining the activities carried out in data collection, analysis, interpretation and presentation. The sample of respondents involved 19 employers and fifty-seven employees from MSE in the MVRSI, eight trainers and four focus groups‘ discussion of eight students each from four TVET institutions, and four government officers.

Case study research methodology has been outlined, and the justification of its use advanced. To collect data, semi-structured interviews were used in businesses, training institutions and government departments. The coordination of four focus group discussion with the final year learners in institutions gave the students an opportunity to offer their input on the training they received. In addition, observations were made in the MSE and institutions, while secondary data in the form of documents were collected from government departments, institutions and business organisations. Methods of data analysis and interpretation have been summarised.

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CHAPTER 6 FINDINGS

6.1 Introduction

This chapter presents data from the interviews, focus group (FG) discussions and observations carried out concerning the three phases of a training and development (T&D) framework. The chapter starts by presenting profiles of the respondents involved in this research. Then in sections 6.3 and 6.4, a discussion of the findings of the first phase of a T&D model—the training and development needs assessment (T&DNA) phase. This phase is sub-divided into training needs analysis (TNA) and training objectives. In section 6.5, findings of the stakeholders‘ views of the second phase of T&D—the training processes or training activities in Kenya‘s Motor Vehicle Repair and Service Industry (MVRSI) is presented. This phase involves the activities carried out in the curriculum implementation that includes designing the training program and using different methods to achieve stated objectives. Then in section 6.6, the processes of the TVET program‘s evaluation is discussed as outlined by the education officials and trainers. Further, since all employers that took part in this study carried out some form of training, their evaluation processes have been outlined.